CC BY-NC-ND 4.0 · Yearb Med Inform 2018; 27(01): 146-155
DOI: 10.1055/s-0038-1641217
Section 7: Consumer Health Informatics and Education
Survey
Georg Thieme Verlag KG Stuttgart

Consumer Health Informatics Adoption among Underserved Populations: Thinking beyond the Digital Divide

Jina Huh
1   Michigan State University, MI, USA
,
Jejo Koola
2   University of California San Diego, CA, USA
,
Alejandro Contreras
3   Institute for Behavioral and Community Health, San Diego State University, CA, USA
,
Alanah KP. Castillo
3   Institute for Behavioral and Community Health, San Diego State University, CA, USA
,
Melissa Ruiz
3   Institute for Behavioral and Community Health, San Diego State University, CA, USA
,
Keely G. Tedone
3   Institute for Behavioral and Community Health, San Diego State University, CA, USA
,
Melissa Yakuta
3   Institute for Behavioral and Community Health, San Diego State University, CA, USA
,
Melody K. Schiaffino
3   Institute for Behavioral and Community Health, San Diego State University, CA, USA
› Author Affiliations
Further Information

Publication History

Publication Date:
29 August 2018 (online)

Summary

Objectives: Underserved populations can benefit from consumer health informatics (CHI) that promotes self-management at a lower cost. However, prior literature suggested that the digital divide and low motivation constituted barriers to CHI adoption. Despite increased Internet use, underserved populations continue to show slow CHI uptake. The aim of the paper is to revisit barriers and facilitators that may impact CHI adoption among underserved populations.

Methods: We surveyed the past five years of literature. We searched PubMed for articles published between 2012 and 2017 that describe empirical evaluations involving CHI use by underserved populations. We abstracted and summarized data about facilitators and barriers impacting CHI adoption.

Results: From 645 search results, after abstract and full-text screening, 13 publications met the inclusion criteria of identifying barriers to and facilitators of underserved populations' CHI adoption. Contrary to earlier literature, the studies suggested that the motivation to improve health literacy and adopt technology was high among studied populations. Beyond the digital divide, barriers included: low health and computer literacy, challenges in accepting the presented information, poor usability, and unclear content. Factors associated with increased use were: user needs for information, user-access mediated by a proxy person, and early user engagement in system design.

Conclusions: While the digital divide remains a barrier, newer studies show that high motivation for CHI use exists. However, simply gaining access to technology is not sufficient to improve adoption unless CHI technology is tailored to address user needs. Future interventions should consider building larger empirical evidence on identifying CHI barriers and facilitators.

 
  • References

  • 1 van Dijk J. Digital divide research, achievements and shortcomings. Poetics 2006; Aug 1; 34 (04) 221-235
  • 2 Chang BL, Bakken S, Brown SS, Houston TK, Kreps GL, Kukafka R. , et al. Bridging the digital divide: reaching vulnerable populations. J Am Med Inform Assoc 2004; Nov 11 (06) 448-457
  • 3 Jimison H, Gorman P, Woods S, Nygren P, Walker M, Norris S. , et al. Barriers and drivers of health information technology use for the elderly, chronically ill, and underserved. Evid Rep Technol Assess 2008; Nov 175: 1-1422
  • 4 NORC at the University of Chicago. Understanding the impact of health IT in underserved communities and those with health disparities. The United States Department of Health and Human Services; 2010 Oct. Report No.: HHSP23320095635WC.
  • 5 Christopher Gibbons M. Use of health information technology among racial and ethnic under-served communities. Perspect Health Inf Manag 2011; Jan 1; 8: 1f
  • 6 Poushter J. Smartphone ownership and internet usage continues to climb in emerging economies. Pew Research Center [Internet]. 2016;22. Available from: http://s1.pulso.cl/wp-content/uploads/2016/02/2258581.pdf
  • 7 Clark SJ, Butchart A, Kennedy A, Dombkowski KJ. Parents’ experiences with and preferences for immunization reminder/recall technologies. Pediatrics 2011; Nov 128 (05) e1100-e1105
  • 8 Malvey D, Slovensky DJ. mHealth: Transforming Healthcare. Springer; 2014
  • 9 Lopez MH, Gonzalez-Barrera A, Patten E. Closing the digital divide: Latinos and technology adoption [Internet]. Pew Research Center; 2013. Available from: http://assets.pewresearch.org/wp-content/uploads/sites/7/2013/03/Latinos_Social_Media_and_Mobile_Tech_03-2013_final.pdf
  • 10 Ryu B, Kim N, Heo E, Yoo S, Lee K, Hwang H. , et al. Impact of an Electronic Health Record-Integrated Personal Health Record on Patient Participation in Health Care: Development and Randomized Controlled Trial of MyHealthKeeper. J Med Internet Res 2017; Dec 7; 19 (12) e401
  • 11 Suna T. Finnish national archive of health information (KanTa): General concepts and information model. Fujitsu Sci Tech J 2011; 47 (01) 49-57
  • 12 Efobi U, Tanankem B, Asongu S. Female Economic Participation With Information and Communication Technology (ICT) Advancement: Evidence From Sub-Saharan Africa. South African Journal of Economics [Internet] 2018 Jan 3 [cited 2018 May 3]; Available from: https://papers.ssrn.com/abstract=3170739
  • 13 Chang AY, Ghose S, Littman-Quinn R, Anolik RB, Kyer A, Mazhani L. , et al. Use of mobile learning by resident physicians in Botswana. Telemed J E Health 2012; Jan 18 (01) 11-13
  • 14 Lester RT, Ritvo P, Mills EJ, Kariri A, Karanja S, Chung MH. , et al. Effects of a mobile phone short message service on antiretroviral treatment adherence in Kenya (WelTel Kenya1): a randomised trial. Lancet 2010; Nov 27; 376 (9755): 1838-1845
  • 15 Adedeji AA, Sanusi B, Tella A, Akinsanya M, Ojo O, Akinwunmi MO. , et al. Exposure to anti-malarial drugs and monitoring of adverse drug reactions using toll-free mobile phone calls in private retail sector in Sagamu, Nigeria: implications for phar-macovigilance. Malar J 2011; Aug 9; 10 (01) 230
  • 16 Laxman K, Krishnan SB, Dhillon JS. Barriers to adoption of consumer health informatics applications for health self management. Health Science Journal 2015; 9 (05) 1
  • 17 Hung M, Conrad J, Hon SD, Cheng C, Franklin JD, Tang P. Uncovering patterns of technology use in consumer health informatics: Uncovering patterns of technology use. WIREs Comput Stat 2013; Nov 31; 5 (06) 432-447
  • 18 Beard L, Schein R, Morra D, Wilson K, Keelan J. The challenges in making electronic health records accessible to patients. J Am Med Inform Assoc 2012; Jan 1; 19 (01) 116-120
  • 19 Venkatesh V, Morris MG, Davis GB, Davis FD, DeLone WH, McLean ER. , et al. User acceptance of information technology: Toward a unified view. MIS Q 2003; 27 (03) 425-478
  • 20 Venkatesh V, Brown SA. A longitudinal investigation of personal computers in homes: adoption determinants and emerging challenges. MIS Q 2001; 71-102
  • 21 Rogers E. Diffusion of innovations. NewYork, NY: Simon and Schuster; 2010
  • 22 Ramaprasad A, Syn T. An Ontology of Consumer Health Informatics. In: Contemporary Consumer Health Informatics. Springer, Cham 2016; . p. 333-46 . (Healthcare Delivery in the Information Age)
  • 23 Grobler L, Marais BJ, Mabunda S. Interventions for increasing the proportion of health professionals practising in rural and other underserved areas. Cochrane Database Syst Rev 2015; Jun 30; (06) CD005314
  • 24 Committee on Understanding and Eliminating Racial and Ethnic Disparities in Health Care, Board on Health Sciences Policy, Institute of Medicine. Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care (with CD). National Academies Press; 2009
  • 25 Committee on Oral Health Access to Services, Board on Health Care Services, Board on Children, Youth and Families, Institute of Medicine, Division of Behavioral and Social Sciences and Education, National Research Council. Improving Access to Oral Health Care for Vulnerable and Underserved Populations. National Academies Press; 2012
  • 26 Medically Underserved Areas and Populations (MUA/Ps) | Bureau of Health Workforce [Internet]. [cited 2018 May 7]. Available from: https://bhw.hrsa.gov/shortage-designation/muap
  • 27 Committee on Understanding and Eliminating Racial and Ethnic Disparities in Health Care, Board on Health Sciences Policy, Institute of Medicine. Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care (with CD). National Academies Press; 2009
  • 28 Committee on Oral Health Access to Services, Board on Health Care Services, Board on Children, Youth and Families, Institute of Medicine, Division of Behavioral and Social Sciences and Education, National Research Council. Improving Access to Oral Health Care for Vulnerable and Underserved Populations. National Academies Press; 2012
  • 29 Medically Underserved Areas and Populations (MUA/Ps) | Bureau of Health Workforce [Internet]. [cited 2018 May 7]. Available from: https://bhw.hrsa.gov/shortage-designation/muap
  • 30 Grant MJ, Booth A. A typology of reviews: an analysis of 14 review types and associated methodologies. Health Info Libr J 2009; Jun 26 (02) 91-108
  • 31 Daly J, Kellehear A, Gliksman M. The public health researcher: A methodological approach. Melbourne, Australia: Oxford University Press; 1997
  • 32 Rice PL, Ezzy D. Qualitative research methods: A health focus. Melbourne, Australia [Internet]. 1999; Available from: https://pdfs.semanticscholar.org/6455/3eeb64d62e2ff1bb501bcf360c1b-024fa140.pdf#page=47
  • 33 Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JPA. , et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration. BMJ 2009; Jul 21; 339: b2700
  • 34 Damman OC, Bogaerts NMM, van Dongen D, Timmermans DRM. Barriers in using cardiomet-abolic risk information among consumers with low health literacy. Br J Health Psychol 2016; Feb 21 (01) 135-156
  • 35 Kukafka R, Yi H, Xiao T, Thomas P, Aguirre A, Smalletz C. , et al. Why Breast Cancer Risk by the Numbers Is Not Enough: Evaluation of a Decision Aid in Multi-Ethnic, Low-Numerate Women. J Med Internet Res 2015; Jul 14; 17 (07) e165
  • 36 Owens OL, Friedman DB, Brandt HM, Bernhardt JM, Hébert JR. An Iterative Process for Developing and Evaluating a Computer-Based Prostate Cancer Decision Aid for African American Men. Health Promot Pract 2015; Sep 16 (05) 642-655
  • 37 Rosas LG, Trujillo C, Camacho J, Madrigal D, Bradman A, Eskenazi B. Acceptability of health information technology aimed at environmental health education in a prenatal clinic. Patient Educ Couns 2014; Nov 97 (02) 244-247
  • 38 Cogbill S, Francis B, Sanders Thompson VL. Factors affecting African American men's use of online colorectal cancer education. J Cancer Educ 2014; Mar 29 (01) 25-29
  • 39 Bass SB, Gordon TF, Ruzek SB, Wolak C, Ruggieri D, Mora G. , et al. Developing a computer touchscreen interactive colorectal screening decision aid for a low-literacy African American population: lessons learned. Health Promot Pract 2013; Jul 14 (04) 589-598
  • 40 Neuenschwander LM, Abbott A, Mobley AR. Comparison of a web-based vs in-person nutrition education program for low-income adults. J Acad Nutr Diet 2013; Jan 113 (01) 120-126
  • 41 Ancker JS, Mauer E, Hauser D, Calman N. Expanding access to high-quality plain-language patient education information through context-specific hyperlinks. AMIA Annu Symp Proc 2016; 2016: 277-84
  • 42 Gordon NP, Hornbrook MC. Differences in Access to and Preferences for Using Patient Portals and Other eHealth Technologies Based on Race, Ethnicity, and Age: A Database and Survey Study of Seniors in a Large Health Plan. J Med Internet Res 2016; Mar 4; 18 (03) e50
  • 43 Smith SG, O'Conor R, Aitken W, Curtis LM, Wolf MS, Goel MS. Disparities in registration and use of an online patient portal among older adults: findings from the LitCog cohort. J Am Med Inform Assoc 2015; Jul 22 (04) 888-895
  • 44 Odlum M, Gordon P, Camhi E, Valdez E, Bakken S. Exploring factors related to the adoption and acceptance of an internet-based electronic personal health management tool (EPHMT) in a low income, special needs population of people living with HIV and AIDS in New York City. Stud Health Technol Inform 2014; 201: 145-52
  • 45 Czaja SJ, Loewenstein D, Schulz R, Nair SN, Perdomo D. A videophone psychosocial intervention for dementia caregivers. Am J Geriatr Psychiatry 2013; Nov 21 (11) 1071-1081
  • 46 Lapane KL, Goldman RE, Quilliam BJ, Hume AL, Eaton CB. Tailored DVDs: a novel strategy for educating racially and ethnically diverse older adults about their medicines. Int J Med Inform 2012; Dec 81 (12) 852-860
  • 47 Montague E, Perchonok J. Health and wellness technology use by historically underserved health consumers: systematic review. J Med Internet Res 2012; May 31; 14 (03) e78
  • 48 Almiron-Roig E, Aitken A, Galloway C, Ellahi B. Dietary assessment in minority ethnic groups: a systematic review of instruments for portion-size estimation in the United Kingdom. Nutr Rev 2017; Mar 75 (03) 188
  • 49 Sakaguchi-Tang DK, Bosold AL, Choi YK, Turner AM. Patient Portal Use and Experience Among Older Adults: Systematic Review. JMIR Med Inform 2017; Oct 16; 5 (04) e38
  • 50 Nambisan P. Patient Portal Readiness (PPR) among the Underserved: Impact of PHIM Activities, Health Information Seeking, and Patient Attitudes towards Record Keeping. In: 2015 48th Hawaifi International Conference on System Sciences; 2015; . p. 2985-91
  • 51 Sakaguchi-Tang DK, Bosold AL, Choi YK, Turner AM. Patient Portal Use and Experience Among Older Adults: Systematic Review. JMIR Med Inform 2017; Oct 16; 5 (04) e38
  • 52 Nambisan P. Factors that impact Patient Web Portal Readiness (PWPR) among the underserved. Int J Med Inform 2017; Jun; 102: 62-70
  • 53 Ohno-Machado L. Focusing on the patient: mHealth, social media, electronic health records, and decision support systems. J Am Med Inform Assoc 2014; Jan 1; 21 (06) 953
  • 54 Neogi PK, Brocca J. Broadband Adoption and Use in Canada and the US: Is the Digital Divide Closing?. SSRN Electronic Journal [Internet]. 2011 ; Available from: http://dx.doi.org/10.2139/ssrn.1983590
  • 55 Krebs P, Duncan DT. Health App Use Among US Mobile Phone Owners: A National Survey. JMIR Mhealth Uhealth 2015; Nov 4; 3 (04) e101
  • 56 Donner J, Escobari MX. A review of evidence on mobile use by micro and small enterprises in developing countries. J Int Dev 2010; Jul 1; 22 (05) 641-658
  • 57 Durand M-A, Carpenter L, Dolan H, Bravo P, Mann M, Bunn F. , et al. Do interventions designed to support shared decision-making reduce health inequalities?. A systematic review and meta-analysis. PLoS One 2014; Apr 15; 9 (04) e94670
  • 58 Boag-Munroe G, Evangelou M. From hard to reach to how to reach: A systematic review of the literature on hard-to-reach families. Research Papers in Education 2012; 27 (02) 209-39
  • 59 Raja S, Hasnain M, Vadakumchery T, Hamad J, Shah R, Hoersch M. Identifying elements of patient-centered care in underserved populations: a qualitative study of patient perspectives. PLoS One 2015; May 19; 10 (05) e0126708
  • 60 Becker SA, Webbe F. Use of handheld technology by older adult caregivers as part of a virtual support network. In: Pervasive Health Conference and Workshops 2006; . p. 1-10
  • 61 Bevan JL, Pecchioni LL. Understanding the impact of family caregiver cancer literacy on patient health outcomes. Patient Educ Couns 2008; Jun 71 (03) 356-364
  • 62 Schaepe KS. Bad news and first impressions: patient and family caregiver accounts of learning the cancer diagnosis. Soc Sci Med 2011; Sep 73 (06) 912-921
  • 63 Tieu L, Sarkar U, Schillinger D, Ralston JD, Ratanawongsa N, Pasick R. , et al. Barriers and Facilitators to Online Portal Use Among Patients and Caregivers in a Safety Net Health Care System: A Qualitative Study. J Med Internet Res 2015; Dec 3; 17 (12) e275
  • 64 Seo H, Erba J, Geana M, Lumpkins C. Calling Doctor Google? Technology Adoption and Health Information Seeking among Low-income African-American Older Adults. Journal of Public Interest Communications
  • 65 Fitzsimmons KA. African-American women who persist in literacy programs: An exploratory study. Urban Rev 1991; Dec 1; 23 (04) 231-50
  • 66 Schiaffino MK, Nara A, Mao L. Language Services In Hospitals Vary By Ownership And Location. Health Aff 2016; Aug 1; 35 (08) 1399-403
  • 67 McBride B, Nguyen LT, Wiljer D, Vu NC, Nguyen CK, O'Neil J. Development of a Maternal, Newborn and Child mHealth Intervention in Thai Nguyen Province, Vietnam: Protocol for the mMom Project. JMIR Res Protoc [Internet] 2018 Jan [cited 2018 May 4]; 7(01). Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5785686/
  • 68 Rathert C, Wyrwich MD, Boren SA. Patient-centered care and outcomes: a systematic review of the literature. Med Care Res Rev 2013; Aug; 70 (04) 351-379
  • 69 Davis K, Schoenbaum SC, Audet A-M. A 2020 vision of patient-centered primary care. J Gen Intern Med 2005; 20 (10) 953-7
  • 70 Finkelstein J, Knight A, Marinopoulos S, Gibbons MC, Berger Z, Aboumatar H. , et al. Enabling patient-centered care through health information technology. Evid Rep Technol Assess 2012; Jun; (206) 1-1531
  • 71 IT leader Edward Happ to head two new information centers at UMSI [Internet]. . The University Record. [cited 2017 Nov 28]. Available from: https://record.umich.edu/articles/it-leader-edward-happ-head-two-new-information-centers-umsi
  • 72 Jones LM, Veinot TC, Pressler SJ. Cell Phone Information Seeking Explains Blood Pressure in African American Women. West J Nurs Res 2018; May; 40 (05) 617-632
  • 73 Stowell E, Lyson MC, Saksono H, Wurth RC, Jimison H, Pavel M. , et al. Designing and Evaluating mHealth Interventions for Vulnerable Populations. In: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI ‘18 [Internet]. 2018. Available from: http://dx.doi.org/10.1145/3173574.3173589
  • 74 Jimison HB, Gordon CM. Decision Support for Patients. . In: Health Informatics 2016; . p. 163-179
  • 75 Greenberg S, Buxton B. Usability Evaluation Considered Harmful (Some of the Time). In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM; 2008; . p. 111-120 . (CHI ‘08).
  • 76 Karwowski W, Soares MM, Stanton NA. Human Factors and Ergonomics in Consumer Product Design: Uses and Applications. CRC Press; 2011
  • 77 Jordan PW, Thomas B, McClelland IL, Weerdmeester B. Usability Evaluation In Industry. CRC Press; 1996
  • 78 Buley L. The User Experience Team of One: A Research and Design Survival Guide. Rosenfeld Media; 2013
  • 79 Summers S, Watt A. Quick and dirty usability testing in the technical communication classroom. In: 2015 IEEE International Professional Communication Conference (IPCC) [Internet]. 2015 . Available from: http://dx.doi.org/10.1109/ipcc.2015.7235831
  • 80 Sauro J. A Practical Guide to the System Usability Scale: Background, Benchmarks & Best Practices. . CreateSpace; 2011
  • 81 Bangor A, Kortum PT, Miller JT. An Empirical Evaluation of the System Usability Scale. Int J Hum Comput Interact 2008; 24 (06) 574-94
  • 82 Lewis JR, Sauro J. The Factor Structure of the System Usability Scale. In: Lecture Notes in Computer Science 2009; . p. 94-103
  • 83 Keh Ann Yunmi, , Keh, Yunmi A. A Comparative Study of Argumentation Structure Between Native and Non-native Speakers of English. English Teaching 2010; 65 (03) 69-95
  • 84 Bangor A, Kortum P, Miller J. Determining what individual SUS scores mean: adding an adjective rating scale. J Usability Stud 2009; May 1; 4 (03) 114-23
  • 85 Peres SC, Camille Peres S, Pham T, Phillips R. Validation of the System Usability Scale (SUS). Proc Hum Fact Ergon Soc Annu Meet 2013; 57 (01) 192-196
  • 86 Gallant LM, Irizarry C, Boone GM, Ruiz-Gordon B. Spanish Content on Hospital Websites: An Analysis of US Hospitals’ in Concentrated Latino Communities. J Comput Mediat Commun 2010; 15 (04) 552-74
  • 87 Murphy PW, Davis TC, Long SW, Jackson RH, Decker BC. Rapid Estimate of Adult Literacy in Medicine (REALM): A Quick Reading Test for Patients. Journal of Reading 1993; 37 (02) 124-130